The use of computing devices by consumers to initiate and carry out payment transactions has greatly increased over time. In many instances, consumers may elect to purchase products using their desktop computer, tablet computer, smart phone, television, or other computing device. The use of a computing device can provide a number of benefits, such as convenience by not having to travel to a merchant's physical location, accessibility for products that may not be locally available to the consumer, or anonymity with regards to the product being purchased and the consumer behind the purchase, such as may be beneficial in the purchasing of surprise gifts.
However, while anonymity and convenience may be beneficial for genuine consumers, the anonymity provided by using a computing device to initiate and carry out a payment transaction may be taken advantage of by nefarious parties wishing to engage in fraud. In such cases, the fraudster may often choose a computing device that is public or otherwise shared among a large number of users that may conduct payment transactions, such as at a public library, Internet café, etc. As a result, it may be more difficult for the fraudster to be detected and differentiated among the large number of users. Accordingly, payment transactions conducted using public or shared computing devices may be at a greater risk for fraud.
However, there is currently a lack of methods available to payment networks, merchants, and financial institutions in detecting when a computing device used in a payment transaction may be public or otherwise shared by a large number of users. Instead, many financial institutions attempt to increase their ability to identify the consumer behind the transaction as an authorized user of the transaction account being used, such as by the use of one-time passwords, security questions, and other authentication mechanisms. Unfortunately, such methods only seek to authenticate the user themselves, and do not identify the usage of the underlying computing device.
Thus, there is a need for a technical solution to identify the number of transaction accounts and/or users associated with a computing device for use in fraud modeling for an attempted payment transaction.